scholarly journals An analysis of contributing mining factors in coal workers’ pneumoconiosis prevalence in the United States coal mines, 1986–2018

2021 ◽  
Author(s):  
Younes Shekarian ◽  
Elham Rahimi ◽  
Naser Shekarian ◽  
Mohammad Rezaee ◽  
Pedram Roghanchi
Keyword(s):  
United States ◽  
Statistical Analysis ◽  
Coal Mines ◽  
The United States ◽  
Mine Safety ◽  
Western Region ◽  
Health Administration ◽  
Underground Coal Mines ◽  
The Western Region ◽  
Coal Workers

AbstractIn the United States, an unexpected and severe increase in coal miners’ lung diseases in the late 1990s prompted researchers to investigate the causes of the disease resurgence. This study aims to scrutinize the effects of various mining parameters, including coal rank, mine size, mine operation type, coal seam height, and geographical location on the prevalence of coal worker's pneumoconiosis (CWP) in surface and underground coal mines. A comprehensive dataset was created using the U.S. Mine Safety and Health Administration (MSHA) Employment and Accident/Injury databases. The information was merged based on the mine ID by utilizing SQL data management software. A total number of 123,589 mine-year observations were included in the statistical analysis. Generalized Estimating Equation (GEE) model was used to conduct a statistical analysis on a total of 29,707, and 32,643 mine-year observations for underground and surface coal mines, respectively. The results of the econometrics approach revealed that coal workers in underground coal mines are at a greater risk of CWP comparing to those of surface coal operations. Furthermore, underground coal mines in the Appalachia and Interior regions are at a higher risk of CWP prevalence than the Western region. Surface coal mines in the Appalachian coal region are more likely to CWP development than miners in the Western region. The analysis also indicated that coal workers working in smaller mines are more vulnerable to CWP than those in large mine sizes. Furthermore, coal workers in thin-seam underground mine operations are more likely to develop CWP.

scholarly journals An Analysis of Contributing Mining Factors in Coal Workers’ Pneumoconiosis Prevalence in the United States Coal Mines, 1986-2018

2021 ◽  
Author(s):  
Younes Shekarian ◽  
Elham Rahimi ◽  
Naser Shekarian ◽  
Mohammad Rezaee ◽  
Pedram Roghanchi
Keyword(s):  
United States ◽  
Statistical Analysis ◽  
Coal Mines ◽  
The United States ◽  
Mine Safety ◽  
Western Region ◽  
Health Administration ◽  
Underground Coal Mines ◽  
The Western Region ◽  
Coal Workers

Abstract In the United States, an unexpected and severe increase in coal miners’ lung diseases in the late 1990s prompted researchers to investigate the causes of the disease resurgence. This study aims to scrutinize the effects of various mining parameters, including coal rank, mine size, mining method, coal seam height, and geographical location on the prevalence of CWP in surface and underground coal mines. A comprehensive dataset was created using the U.S. Mine Safety and Health Administration (MSHA) Employment and Accident/Injury databases. The information was merged based on the mine ID by utilizing SQL data management software. A total number of 123,643 mine-year observations were included in the statistical analysis. Generalized Estimating Equation (GEE) model was used to conduct a statistical analysis on a total of 29,707, and 32,643 mine-year observations for underground and surface coal mines, respectively. The results of the econometrics approach revealed that coal workers in underground coal mines are at a greater risk of CWP comparing to those of surface coal operations. Furthermore, underground coal mines in the Appalachia and Interior regions are at a higher risk of CWP prevalence than the Western region. Surface coal mines in the Appalachian coal region are more susceptible to CWP than miners in the Western region. The analysis also indicated that coal workers working in smaller mines are more vulnerable to CWP than those in large mine sizes. Furthermore, coal workers in thin-seam underground mine operations are more likely to develop CWP.

scholarly journals Risk management: Adapting Riskgate for underground coal mines in the United States

2016 ◽  
Vol 68 (3) ◽  
pp. 51-57 ◽  
Author(s):  
E.C. Jong ◽  
J.A. Restrepo ◽  
K.D. Luxbacher ◽  
P.A. Kirsch ◽  
R. Mitra ◽  
...  
Keyword(s):  
United States ◽  
Risk Management ◽  
Coal Mines ◽  
The United States ◽  
Underground Coal Mines

JAUNDICE IN ARMY PERSONNEL IN THE WESTERN REGION OF THE UNITED STATES AND ITS RELATION TO VACCINATION AGAINST YELLOW FEVER1

1944 ◽  
Vol 39 (3) ◽  
pp. 337-430 ◽  
Author(s):  
W. A. SAWYER ◽  
K. P. MEYER ◽  
M. D. EATON ◽  
J. H. BAUER ◽  
PERSIS PUTNAM ◽  
...  
Keyword(s):  
United States ◽  
The United States ◽  
Western Region ◽  
The Western Region ◽  
Army Personnel

JAUNDICE IN ARMY PERSONNEL IN THE WESTERN REGION OF THE UNITED STATES AND ITS RELATION TO VACCINATION AGAINST YELLOW FEVER

1944 ◽  
Vol 40 (1) ◽  
pp. 35-107 ◽  
Author(s):  
W. A. SAWYER ◽  
K. F MEYER ◽  
M. D EATON ◽  
J. H BAUER ◽  
PERSIS PUTNAM ◽  
...  
Keyword(s):  
United States ◽  
Yellow Fever ◽  
The United States ◽  
Western Region ◽  
The Western Region ◽  
Army Personnel

scholarly journals Classifying Large Wildfires in the United States by Land Cover

2020 ◽  
Vol 12 (18) ◽  
pp. 2966
Author(s):  
Brice B. Hanberry
Keyword(s):  
United States ◽  
Random Forests ◽  
Open Space ◽  
The United States ◽  
Western Region ◽  
Eastern Region ◽  
Herbaceous Vegetation ◽  
Extreme Gradient Boosting ◽  
Large Fires ◽  
The Western Region

Fire is an ecological process that also has socio-economic effects. To learn more about fire occurrence, I examined relationships between land classes and about 12,000 spatially delineated large wildfires (defined here as uncontrolled fires ≥200 ha, although definitions vary) during 1999 to 2017 in the conterminous United States. Using random forests, extreme gradient boosting, and c5.0 classifiers, I modeled all fires, first years (1999 to 2002), last years (2014 to 2017), the eastern, central, and western United States and seven ecoregions. The three classifiers performed well (true positive rates 0.82 to 0.94) at modeling all fires and fires by year, region, and ecoregion. The random forests classifier did not predict to other time intervals or regions as well as other classifiers and models were not constant in time and space. For example, the eastern region overpredicted fires in the western region and models for the western region underpredicted fires in the eastern region. Overall, greater abundance of herbaceous grasslands, or herbaceous wetlands in the eastern region, and evergreen forest and low abundance of crops and pasture characterized most large fires, even with regional differences. The 14 states in the northeastern United States with no or few large fires contained limited herbaceous area and abundant crops or developed lands. Herbaceous vegetation was the most important variable for fire occurrences in the western region. Lack of crops was most important for fires in the central region and a lack of pasture, crops, and developed open space was most important for fires in the eastern region. A combination of wildlands vegetation was most influential for most ecoregions, although herbaceous vegetation alone and lack of pasture, crops, and developed open space also were influential. Despite departure from historical fire regimes, these models demonstrated that herbaceous vegetation remains necessary for fires and that evergreen forests in particular are fire-prone, while reduction of vegetation surrounding housing developments will help provide a buffer to reduce large fires.

Causal Factors of Collision Accidents Involving Underground Coal Mobile Equipment

2017 ◽  
Author(s):  
James Noll ◽  
Cory DeGennaro ◽  
Jacob Carr ◽  
Joseph DuCarme ◽  
Gerald Homce
Keyword(s):  
Occupational Safety ◽  
The United States ◽  
Mine Safety ◽  
Health Administration ◽  
Underground Coal Mining ◽  
Causal Factors ◽  
Detection Systems ◽  
Proximity Detection ◽  
Safety And Health ◽  
Underground Coal Mines

From 2000–2015, thirty-two fatalities occurred due to collisions involving mobile equipment in underground coal mining in the United States. Studies have shown that proximity detection systems (PDS) can be a potential mitigation strategy for this type of accident. However, the effectiveness of this approach for mobile equipment has yet to be fully studied or validated. Researchers at the National Institute for Occupational Safety and Health (NIOSH) evaluated the causal factors of this type of fatality. Fatal accident reports from the Mine Safety and Health Administration (MSHA) accident report database provided details to analyze and determine causal factors and to evaluate whether a PDS may have been a preventive factor in each accident. NIOSH researchers concluded that PDSs used in underground coal mines on mobile equipment which are designed to detect a miner, provide warning to the operator and other miners, and automatically stop the machine before a miner is hit may have helped to prevent 25 of the 32 or 78% of the accidents.

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